ProcessMind Launches Process Simulation for Digital Twins

AMSTERDAM, NETHERLANDS

ProcessMind, a European process mining company, announced today the launch of a process simulation engine that helps you create digital twins of business processes. You can build virtual replicas of your operations and test changes in a simulated environment.

AMSTERDAM, NETHERLANDS

Digital Twins in Business Operations

A digital twin is a virtual model of a real-world process in a digital environment. Unlike a static diagram, it uses operational data and updates as the process changes. You can monitor performance, run simulations, and assess potential outcomes before you implement changes.

Digital twin technology, first developed for aerospace and manufacturing, has expanded into business operations. According to Strategic Market Research, the digital twin market was valued at USD 6.30 billion in 2021 and is projected to reach USD 131.09 billion by 2030.

Technical Overview

The ProcessMind process simulation engine extracts parameters from uploaded event logs, including case arrival rates, activity durations, routing probabilities, and resource requirements. You can use these parameters to build digital twins for scenario analysis.

The system uses discrete event simulation (DES), a methodology in which the system state changes at specific events. This approach suits business processes where activities have defined start and end times, resources are allocated at specific moments, and cases follow distinct paths through the process.

Process improvement has always involved guesswork. You make a change and hope it works. With digital twins, you can test ten different scenarios in an afternoon and choose the one most likely to succeed.

Christiaan Esmeijer, Founder of ProcessMind

Capabilities

The simulation engine includes the following capabilities:

• Parameter extraction from event log data
• Scenario modeling with adjustable variables
• Side-by-side comparison of multiple scenarios
• Resource capacity analysis and utilization forecasting
• Bottleneck identification under different volume scenarios
• Support for multiple probability distributions

The engine supports standard probability distributions, including normal, exponential, uniform, triangular, and log-normal. You can configure each activity with processing times, resource requirements, and skip probabilities.

Platform Integration

The simulation engine integrates with ProcessMind’s existing process mining and BPMN modeling capabilities. The platform is hosted in EU data centers and is GDPR-compliant.

The intended workflow is to discover a process through mining, build a digital twin from the extracted data, and simulate proposed changes.

The simulation engine extracts parameters directly from event logs, reducing the manual configuration typically required for process simulation.

Christiaan Esmeijer, Founder of ProcessMind

Application Areas

Typical use cases for process digital twins include testing resource reallocation scenarios, evaluating process redesigns, predicting capacity requirements as volumes change, comparing automation scenarios, and validating proposed solutions before implementation.

The simulation runs virtual process instances through the model using timing distributions, resource capacities, and arrival patterns derived from the source data. The output includes predictions for cycle time, throughput, resource utilization, and cost.